Attempts are now underway worldwide to analyse the molecular biology of cancer causation, specifically to identify the genes whose functions are compromised by mutation or otherwise during cancer development. The rationale for this approach is that such knowledge will aid not only cancer treatment regimes, but also prevention and early detection of cancer. As a corollary, it is also important to examine pre-malignant tissues for such altered gene function. Recent data from our laboratory has shown that the oncogene cyclin D1 and the tumor suppressor gene p16 are frequently altered in SCC. Studies of loss of heterozygosity (LOH) in SCC of the head and neck suggest involvement of other, as yet unidentified genes in the disease. The Specific Aims of this proposal are designed to: First, determine the frequency and nature of genetic changes which occur in oncogene cyclin D1 and tumor suppressor gene p16 in SCC and investigate the hypothesis that changes to these genes may also be present in oral pre-malignant lesions (leukoplakia and/or erythroplakia) capable of progression to SCC. Second, identify other, novel genes expressed in normal oral mucosa but absent from SCC, since such genes may potentially be tumor suppressor genes or be important markers for disease progression. Specific Aim 1 will be achieved by analysis of a sample population comprising a total of 100 SCC specimens (50 oral cavity and 50 larynx/pharynx) and matched normal tissue. Specific Aim 2 will be achieved by comparative analysis of gene expression in positive neck nodes derived from oral SCC and matched tissue derived from normal oral mucosa. Nodal tissue will be used in preference to tissues from primary tumors since usage will preclude tumor sample contamination with normal oral epithelium. Additionally, we have observed a preliminary association between the category of alteration to the p16 gene (point mutation of deletion) and tumor site (oral cavity or larynx/pharynx respectively). One mutational status of p16 in the above 100 SCC is established, data will be analysed by statistical methods to determine whether a positive correlation between tumor site and category of mutation exists.